Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

17 May 2012

Applying Expertise

Clark @ 6:43 AM

I’m trying to get my mind around how the information we’re finding out about expertise matches to the types of problems people face.  Clearly, you want to align your investments appropriately to situations you face.  If you look across the literature on expertise, and the recent writing on how our brains work (c.f. Kahneman’s Thinking Fast and Slow), you see an emerging picture of expertise.  When you combine this with the situations organizations are increasingly facing, you recognize that we need to get more granular about the types of problems we’re facing and the solutions we have on tap.

Starting with the types of problems, there are more than just the problems we know and the ones we don’t.  When you look at the Cynefin model, which characterizes the types of problems we face, we see what types of expertise are helpful.  Beyond work that should be automated, there are formulaic types of complicated problems that can be outsourced or accomplished by skilled or well-supported practitioners.  Then there are the complex problems that require deeper expertise.  Beyond that is the chaotic state where you have to try something to move it into one of the other states, and there are certainly reasons to believe that deep expertise .

So now we look at what’s known about our knowledge.  We’ve known for a while that expertise is slowly accumulated, and becomes deeper in ways that are hard to unpack (hence why you need some detailed approaches to get at their understanding).  What’s also becoming clear is that this ability to make expert judgements, once compiled away, is most effective in quick (not laborious) application, with a caveat.  As Kahneman tells us, this expertise needs to be developed in a field that is “sufficiently regular to be predictable”, and in which the expert gets quick and decisive feedback on whether he did the right or the wrong thing. Otherwise, you need to do the hard yards, the slow thinking that’s effortful and systematic.  Now, if it’s out of your area of expertise but a known problem, you have two choices: either take a well-known (and appropriate) but laborious approach, or hire the appropriate expertise.  If it’s a relatively novel situation, either unique or new, you’ll need a different type of expertise.

We can infer that having a rich suite of models and frameworks helps in circumstances where the right solution isn’t obvious.  The conclusion is clear: advanced experts may not immediately know the solution if the problem is reasonably complex (if so, you can get by with a practitioner), but their deeply developed intuition, based upon experience, and associated approaches to those types of problems will have a higher likelihood of finding a solution.  Particularly if their expertise spans problem-solving in general, and specific expertise in at least some of the involved domains. Experience solving complex problems, and having a deep and broad conceptual background increases the likelihood of a systemic and comprehensive solution.

To think about it another way, this article makes a distinction between puzzles and mysteries. Puzzles have an answer, once you identify the information needed, collect it, and execute against it. This is the ‘Complicated’ part of the Cynefin situation. Mysteries are where you can’t know what will happen, and you have to experiment.  This is the ‘Complex’ or ‘Chaotic’ parts of the model.  You’re better off in the latter two if you’ve got good systems thinking, and a suite of useful models in your quiver.

So, when facing a problem, you have to characterize it: is this a puzzle where someone has an off-the-shelf solution “ah, we know that pain, and we solve it this way”, versus the mystery situation where it’s not clear how things will sort out, and you need a much richer conceptual background to address it. In the former case, you can find vendors or consultants with specific expertise.  In the latter, the implication clearly is that you want someone who’s been thinking and doing this stuff as long as possible.  You want someone who can guide some experiments.

The risk of trying to solve the complex problems with off-the-shelf solutions or DIY is that your answer is likely to be missing a significant component of the situation, and consequently the solution will be partial. You need the right type of expertise for the right type of problem.

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